Training power models using network data

ABSTRACT

Power models may be used to identify devices in a building or state changes of devices in a building by processing a power monitoring signal with the power models. A power model for a device may be trained using examples of power monitoring signals corresponding to that device, and network monitoring may be used to identify training data for training power models for that device. Network monitoring may include receiving information about network packets transmitted by devices in the building and processing the information about the network packets to determine information about a state change of a first device in the building at a first time. A portion of the power monitoring signal that includes the first time may then be used to train a power model for the first device. The trained power model for the first device may then be deployed to a building where it used to perform power monitoring of the first device.

BACKGROUND

Reducing electricity or power usage provides the benefits, among others,of saving money by lowering payments to electric companies and alsoprotecting the environment by reducing the amount of resources needed togenerate the electricity. Electricity users, such as consumers,businesses, and other entities, may thus desire to reduce theirelectrical usage to achieve these benefits. Users may be able to moreeffectively reduce their electricity usage if they have informationabout what devices (e.g., refrigerator, oven, dishwasher, furnace, andlight bulbs) in their homes and buildings are using the most electricityand what actions are available to reduce electricity usage.

Power monitors for individual devices are available for measuring thepower usage of a single device. For example, a device can be pluggedinto a power monitor, and the monitor can in turn be plugged into a walloutlet. These monitors can provide information about power usage for theone device they are attached to, but it may not be practical to monitorall or even many devices in a house or building with these monitors,because it would require a large number of devices that can be expensiveand also require significant manual effort to install.

Instead of a power monitor for a single device, a power monitor can beinstalled at an electrical panel to obtain information about electricityused by many devices simultaneously. A power monitor on an electricalpanel is more convenient because a single monitor can provide aggregateusage information about many devices. It is more difficult, however, toextract more specific information about usage of power by a singledevice, since the monitor typically measures signals that reflect thecollective operation of many devices, which may overlap in complex ways.The process of obtaining information about the power usage of a singledevice from an electrical signal corresponding to usage by many devicesmay be referred to as disaggregation.

To provide the greatest benefits to end users, a need exists for moreaccurate disaggregation techniques, so that end users receive accurateinformation about the electrical usage of individual devices.

BRIEF DESCRIPTION OF THE FIGURES

The invention and the following detailed description of certainembodiments thereof may be understood by reference to the followingfigures:

FIG. 1 is an example of a system for identifying devices and statechanges of devices using a power monitoring signal.

FIG. 2 is an example of a power monitoring signal.

FIG. 3 is an example of a system for identifying devices and statechanges of devices using network data.

FIGS. 4A, 4B, and 4C illustrate techniques for identifying devices andstate changes of devices using network data.

FIG. 5 is an example of a system identifying devices and state changesof devices.

FIG. 6 is an example list of devices.

FIG. 7 is an example of a system for identifying devices and statechanges of devices using a power monitoring signal and network data.

FIGS. 8A and 8B are example timelines of a power monitoring signal andnetwork data.

FIG. 9 is a flowchart showing an example implementation of identifyingdevices using a power monitoring signal and network data.

FIG. 10 is a flowchart showing an example implementation of identifyingstate changes of devices using a power monitoring signal and networkdata.

FIG. 11 is a flowchart showing an example implementation training apower model using network data.

FIG. 12 is an example of a device for identifying devices and statechanges of devices using a power monitoring signal or network data.

DETAILED DESCRIPTION

Described herein are techniques for identifying devices and determininginformation about state changes of devices in a building. One source ofdata in determining information about devices in a building is theelectrical line that provides power to the devices in the building.Electrical sensors may be placed on the electrical line (or lines) thatare providing power to the building, and disaggregation techniques maybe used to determine information about individual devices in thebuilding. For example, any of the techniques described in U.S. Pat. No.9,443,195, which is hereby incorporated by reference in its entirety forall purposes, may be used to determine information about devices usingelectrical measurements.

Another source of data for identifying devices or determininginformation about device state changes in a building is a computernetwork in the building. A building may have a network, such as a localarea network, and devices may connect to the network via a wire (e.g.,an Ethernet cable) or wirelessly (e.g., Wi-Fi). A building may havemultiple networks, such as local area network coordinated by a wirelessrouter, a mesh network created by other devices working in cooperation(e.g., Sonos speakers), and a personal area network (e.g., a Bluetoothconnection between devices). Information about devices on these networksmay be obtained, for example by receiving a service broadcast from adevice after it is turned on or by polling a device for information.

Some devices may be powered by the electrical line in the building butmay not have a network connection (e.g., a conventional refrigerator).Some devices may be powered by the electrical line in the building andhave a network connection (e.g., a “smart” refrigerator). Some devicesmay have a network connection but may not by powered by the electricalline (e.g., mobile devices, such as smartphones) or may only sometimesbe powered by the electrical line (e.g., when charging). The techniquesdescribed herein may provide more information and/or more accurateinformation about devices in the building by using a combination ofinformation from the electrical line and information from a network inthe building.

The information from the electrical line and from the network in thebuilding may be used to provide a service to users to inform them aboutthe status of devices in the building. A company may provide a powermonitoring device that may be installed in the building and connected toboth the power line and the computer network of the building. The powermonitoring device may use both the electrical line and network data todetermine information about what devices are present in the building andalso the states of the devices (e.g., on or off). This information maythen be made available to the user, such as by presenting it in aspecialized app (e.g., on a smartphone) or a web page. The service mayprovide the user with information about devices in the building, such asreal-time information about the states of devices, real-time power usageby devices, and historical information about device activity.

For clarity of presentation, the techniques described herein will use ahouse or home as an example of a building where the techniques may beapplied, but the techniques described herein are equally applicable toany environment where electricity is used, including but not limited tobusinesses and commercial buildings, government buildings, and othervenues. References to homes throughout should be understood to encompasssuch other venues.

Power Monitoring

FIG. 1 illustrates an example of a system 100 where information obtainedfrom an electrical line may be used to determine information aboutdevices in a home. In FIG. 1, electric company 120 provides electricalpower to home 110. The electrical power is transmitted to an electricalpanel 140 where it may then be distributed to different electricalcircuits in the house.

Electrical panel 140 may be any electrical panel that may be found in abuilding. For example, electrical panel 140 may implement split-phaseelectric power, where a 240 volt AC electrical signal is converted witha split-phase transformer to a three-wire distribution with a singleground and two mains (or legs) that each provide 120 volts. Some devicesin the house may use one of the two mains to obtain 120 volts; otherdevices in the house may use the other main to obtain 120 volts; and yetother devices may use both mains simultaneously to obtain 240 volts.

Any type of electrical panel may be used, and the techniques describedherein are not limited to a split phase electrical panel. For example,electrical panel 140 may be single phase, two phase, or three phase. Thetechniques are also not limited to the number of mains provided byelectrical panel 140. In the discussion below, electrical panel 140 willbe described as having two mains, but any number of mains may be used,including just a single main. Other voltage standards, such as for othercountries or continents, are intended to be encompassed herein as wouldbe understood by one of ordinary skill in the art.

FIG. 1 illustrates devices that are consuming electricity provided byelectrical panel 140. For example, power monitor 150, refrigerator 160,and stove 165 may consume electricity provided via electrical panel 140.

Power monitor 150 may be connected to sensor 130 to measure electricalproperties of the electrical line connected to house 110. For example,sensor 130 may measure voltage and/or current levels for electricallines providing electricity to electrical panel 140. The measurementsmay be obtained using any available sensors, and the techniques are notlimited to any particular sensors or any particular types of values thatmay be obtained from sensors. Sensor 130 may comprise multiple sensors,such as one or more sensors for each main.

Sensor 130 may provide one or more power monitoring signals to powermonitor 150, such as a measurement of current and/or voltage for eachmain connected to electrical panel 140. Power monitor 150 may processthe power monitoring signals to disaggregate them or to obtaininformation about individual devices in the home. For example, powermonitor 150 may determine state changes of devices, such as thetelevision was turned on at 8:30 pm or the compressor of therefrigerator started at 10:35 am and 11:01 am.

Power monitor 150 may be a device that is obtained separately fromelectrical panel 140 and installed by a user or electrician to connectto electrical panel 140. Power monitor 150 may be part of electricalpanel 140 and installed by the manufacturer of electrical panel 140.Power monitor 150 may also be part of (e.g., integrated with or into) anelectrical meter, such as one provided by the electric company, andsometimes referred to as a smart meter.

Power monitor 150 may use any appropriate techniques for performingdisaggregation or determining information about the power usage or stateof individual devices from the power monitoring signal. For example,power monitor 150 may use any of the techniques described in U.S. Pat.No. 9,443,195.

FIG. 2 illustrates an example of a hypothetical power monitoring signal200 that may be processed by power monitor 150. FIG. 2 illustrateschanges to the power monitoring signal caused by state changes of twodevices, a stove and an incandescent light bulb. Each of the changes inthe power signal may be referred to as a power event. In FIG. 2, thepower events labelled with HE1 correspond to a heating element of theburner of a stove being turned on and the power events labelled with HE0correspond to a heating element of the burner being turned off (forelectric stoves, the burner may appear to be on to the user, but thestove may cause the heating element to turn on and off on a periodicbasis to maintain a desired temperature). The power event labelled withI1 corresponds to an incandescent light bulb being turned on and thepower event labelled I0 corresponds to the incandescent light bulb beingturned off.

At power event 210, a burner of a stove is turned on and the heatingelement of the burner consumes electricity. Accordingly, the power usageincreases in the power monitoring signal. While the heating element ison, at power event 220, the incandescent light bulb is turned on tofurther increase the power usage. At power events 230, 240, 250, and260, the heating element is turned off, then on, then off, and then onagain. At power event 270, the incandescent light bulb is turned off,and at power event 280, the burner of the stove is turned off and theheating element stops consuming electricity.

Power monitor 150 may process the power monitoring signal 200 toidentify devices and/or determine state changes of devices. Some statechanges may correspond to a person turning on or off the device and somestate changes may correspond to change in the functioning of a device(e.g., cycling of a heating element or washing machine changing fromwash mode to a spin mode). Power monitor 150 may use any appropriatetechniques for identifying devices and determining state changes ofdevices, such as any of the techniques described in U.S. Pat. No.9,443,195.

In some implementations, power monitor 150 may process a powermonitoring signal with mathematical models to identify devices anddetermine state changes of devices. Such models will be referred to aspower models. For example, power monitor 150 may have power models fordifferent types of devices (e.g., stove, dishwasher, refrigerator,etc.), different makes of devices (e.g., Kenmore dishwasher, Maytagdishwasher, etc.), different versions of devices (e.g., Kenmore 1000dishwasher), and specific devices (e.g., the dishwasher at 100 MainSt.). Power monitor 150 may also have power models for particular statechanges, such as a device turning on, a device turning off, or a devicechanging operation in another way (a water pump of a dishwasher turningon or off). In common usage, the “1000” in a Kenmore 1000 dishwasher maybe referred to as a “model” of the dishwasher, but to avoid confusionwith mathematical models, the “model” of a dishwasher will instead bereferred to herein as a “version.”

When processing the power monitoring signal with a power model, such asany of the power models referred to above, the power model may generatea score (e.g., a probability, likelihood, confidence, etc.) indicating amatch between the power model and the power monitoring signal. When apower event occurs in the power monitoring signal (such as any of theevents in FIG. 2), a portion of the power monitoring signal thatincludes the power event may be processed by a variety of power models,and a score may be generated by each of the power models. The powermodel scores may be used to identify devices in the home and/ordetermine state changes of devices in the home.

In some implementations, power monitoring signal processing may proceedas follows. The power monitoring signal may be continuously processed toidentify power events in the power monitoring signal. Where the powermonitoring signal has a steady value or minor fluctuations, there maynot be any device state changes in the house. A power event detectioncomponent may detect changes in the electrical signal that likelycorrespond to device state changes and cause these portions of the powermonitoring signal to be further processed. A power event detectioncomponent may be implemented using any appropriate techniques, such as aclassifier.

After a power event is detected, a feature generation component may beused to generate features from the portion of the power monitoringsignal that includes the power event. Any appropriate features may becomputed, such as any of the features described in U.S. Pat. No.9,443,195.

The features may then be processed by one or more power models toidentify a device or determine a device state change corresponding tothe power event. Any appropriate power models may be used, such as thetransition models, device models, wattage models, and prior modelsdescribed in U.S. Pat. No. 9,443,195. For example, each power model maygenerate a score, and the device state change may be determined byselecting the power model with the highest score.

Techniques for identifying devices in a home using power models are nowdescribed. In some implementations, power monitor 150 may be installedwith an initial set of power models corresponding to devices that arelikely in the house. As the power monitoring signal is processed, scoresmay be generated for power events that occur in the power monitoringsignal using the power models. These scores may be used to identify whatdevices are in the house.

In some implementations, power monitor 150 may identify a device asbeing in the house if a score generated by a power model exceeds athreshold. For example, a dishwasher model may generate a score thatexceeds a threshold when a dishwasher model processes a portion of thepower monitoring signal corresponding to the dishwasher being started.The threshold may be specific to the dishwasher model or the thresholdmay be the same for all power models. In some implementations, aconfidence level may be computed in addition to or instead of the score,and a device will be identified when the confidence level exceeds athreshold.

In some implementations, additional criteria may be considered beforeidentifying a device. For example, power monitor 150 may have multipledishwasher power models corresponding to different types of dishwashers(e.g., regular dishwashers and energy efficient dishwashers) or theremay be power models for different makes of dishwashers. When processingthe power monitoring signal corresponding to the dishwasher starting,multiple dishwasher models may produce a score (or confidence level)that exceeds the threshold. Instead of identifying multiple dishwashers,a single dishwasher may be identified corresponding to the highestscoring model that exceeds the threshold. For example, power monitor 150may have a power model for Kenmore dishwashers and Bosch dishwashers.Each model may generate a score that exceeds the threshold, but thescore of the Kenmore model may be higher than the score for the Boschmodel. Accordingly, a Kenmore dishwasher may be identified.

In some implementations, power monitor 150 may be updated withadditional power models after a device has been identified. For example,after it has been determined that the house has a dishwasher, powermodels may be added to power monitor 150 corresponding to the mostcommon makes of dishwashers. The power monitoring signal may then beprocessed with the power models for different makes of dishwashers, anda highest scoring power model may be used to identify the make of thedishwasher in the house. This process may be repeated to determineadditional information, such as a version of the dishwasher (e.g.,Kenmore 1000 dishwasher).

After devices in the house have been identified, power monitor 150 mayprocess the power monitoring signal to determine state changes of theidentified devices. In addition to having power models for particulardevices, power monitor 150 may also have models for particular statechanges of devices, and these models may be used to determine when adevice changes state.

As described above, power models for state changes of devices may beused to process a power monitoring signal to generate scores for thepossible state changes. Where a score (or confidence level) exceeds athreshold, power monitor 150 may determine that the state changecorresponding to the model has occurred. For example, power monitor 150may have power models for the dishwasher starting operation andfinishing operation. When the power model for the dishwasher startinggenerates a score that exceeds a threshold, power monitor 150 maydetermine that the dishwasher has started. Similarly, when the powermodel for the dishwasher ending generates a score that exceeds athreshold, power monitor 150 may determine that the dishwasher hasfinished its cycle.

The power models for determining state changes need not be the same asthe power models for identifying devices, and the thresholds used fordetermining state changes need not be the same as the thresholds usedfor identifying devices. The models and thresholds may be adjusted toobtain desired tradeoffs for accuracy and error rates.

Aspects of the operations described above for identifying devices anddetermining state changes of devices may be performed by other computersinstead of power monitor 150 (e.g., a server computer operating inconjunction with a power monitor). For example, in some implementations,power monitor 150 may provide a power monitoring signal to anothercomputer (e.g., a server) and the other computer may identify devicesand state changes. In some implementations, the other computer mayidentify devices, and power monitor 150 may determine state changes ofdevices.

Network Monitoring

In some implementations, power monitor 150 may be connected to acomputer network in the house. For example, power monitor 150 may have awired connection to a router in the house (e.g., LAN Ethernet), may havea wireless connection to a network (e.g., Wi-Fi), or may have directnetwork connections with other devices (e.g., Bluetooth). In theseimplementations, power monitor 150 is also a network monitor, but forclarity of presentation, the following description will continue to usethe term power monitor.

FIG. 3 illustrates an example system 300 where power monitor 150 isconnected to a network in the house. In this example, power monitor 150has a network connection with network device 310, which may be anydevice that facilitates a network in the house, such as a modem, router,or hub. Other devices in the house may also be connected to networkdevice 310. For example, a television 320 (e.g., a smart television),computer 330 (e.g., a personal computer), smart switch 340 (e.g., aPhillips Hue or Belkin Wemo switch), and a phone 360 (e.g., an Androidphone or iPhone) may also be connected to the home network. Powermonitor 150 may connect to other devices in the house using anyappropriate wired or wireless network configuration, such as LANEthernet or direct connections with other devices. In someimplementations, power monitor 150 may communicate on multiple networkssimultaneously (e.g., a Wi-Fi connection to a home router and aBluetooth connection to a specific device).

Power monitor 150 may learn about devices in the house using datatransmitted over the computer network. For example, power monitor 150may listen for broadcast messages from other devices, may poll otherdevices, or may listen for network data generated by other devices. Insome implementations, power monitor 150 may learn about other devices inthe house indirectly via networks outside of the house. For example, adevice in the house may transmit information to a third-party serverthat operates in conjunction with that device, and the third-partyserver may transmit information to a server that operates in conjunctionwith power monitor 150. Each of these techniques may be used to identifydevices in the house and determine state changes of the devices (e.g.,that the device is on or off).

In some implementations, a device in the house may transmit data thatincludes information about the device itself (e.g., a broadcast messageor response to poll). For example, a network transmission may includeany of the following: a state (e.g., device just turned on or will beturning off), services offered by the device, a user assigned name(e.g., “John's Mac”), a make, a hardware version, a software version, anetwork address (e.g., an IP address), an identification number (e.g., aMAC address, a device serial number, a universally unique identifier, aglobally unique identifier, or a temporary identifier), or otherinformation (e.g., protocol-specific identification (such as a Zeroconfservice name) or a resource locator used with the SSDP protocol).

FIG. 4A illustrates an example timeline of power monitor 150 learninginformation about another device by listening for broadcast messagesfrom the other device (a broadcasting device). Some devices may beconfigured to broadcast information across a network to announceservices or capabilities offered by the device to other devices on thenetwork. For example, a television may provide a service to allow otherdevices (e.g., phones or personal computers) to stream video content tothe television for the television to display, and the television maybroadcast a message to the network so that other devices know that thisservice is available.

In FIG. 4A, a broadcasting device transmits a message to announceavailability of a service and later transmits a message to announcewithdrawal of the service. In FIG. 4A, time proceeds from top to bottom,and at 410, the broadcasting device is turned on, such as being turnedon by a person. The broadcasting device may then announce the servicesit provides by broadcasting one or more messages on the network at 411,and this message may be received by other devices on the network,including power monitor 150. Later, the broadcasting device may receivea power off event at 412, such as input (e.g., from a person) to turnitself off. After receiving this input, the broadcasting device maybroadcast a message that the service is being withdrawn to other deviceson the network at 413, and this message may be received by power monitor150. After broadcasting the message, the broadcasting device may turnoff at 414.

Broadcasts are not limited to after a device turns on and before adevice turns off, and broadcasts may be used at any time to announce anychange in services or to remind other devices on the network that theservices are available. For example, a device may broadcast a messagebefore going to sleep or after waking up from being in a sleep mode, toindicate the state of the device, to indicate that the device is in use(e.g., that a song is being played or information about the song beingplayed), or to indicate that a type of media being presented haschanged. In some implementations, devices may broadcast messages usingsimple service discovery protocol (SSDP), zero-configuration networking(zeroconf), or NetBIOS. For example, with SSDP, a device may usemulticast addressing to broadcast a message to all devices on thenetwork.

Information from the broadcast messages may be used to identify devicesin the house. For example, the messages may include data that may beused to identify the device, such as text describing the device or anidentifier. Information from the broadcast messages may also be used todetermine the state of the device. For example, announcing theavailability of a service may indicate that the device is on andannouncing withdrawal of a service may indicate that the device is off.In some implementations, a broadcast message may provide someinformation about the device, and upon receiving the broadcast message,power monitor 150, may poll the device to obtain additional informationabout the state of the device. For example, a network speaker system maybroadcast that services are available, and power monitor 150 may thenpoll the network system to find out that it is currently playing musicand information about the music being played (e.g., song title, volume,etc.)

FIG. 4B illustrates an example timeline of power monitor 150 learninginformation about another device by using polling techniques. Powermonitor 150 may poll other devices one at a time or may poll multipledevices simultaneously, but for clarity of presentation only one polleddevice is shown.

At the beginning of the timeline in FIG. 4B, the polled device is in anoff state. At 420, power monitor 150 polls the polled device, but sincethe polled device is in an off state, the polled device does not respondto the poll request. Power monitor 150 may determine that the polleddevice is in an off state when it does not receive a response to a pollrequest (or perhaps not receiving a response to multiple poll requests).

At 421, the polled device is turned on, for example by a person. At 422,the power monitor 150 again polls the polled device. Since the polleddevice is now on, the polled device responds at 423. After receiving aresponse from the polled device, the power monitor 150 may determinethat the polled device has transitioned from an off state to an onstate. Poll responses may include information that may be used todetermine the state of the device, as described in greater detail below.The poll response may include any of the information described above forbroadcast messages.

At 424, the power monitor 150 again polls the polled device, and at 425the polled device responds to the poll request so the power monitor 150can determine that the polled device is still in an on state. At 426,the polled device is turned off. At 427, power monitor 150 again pollsthe polled device and does not receive a response so the power monitor150 may determine that the polled device is now in an off state.

Any appropriate polling techniques may be used to poll a device. In someimplementations, the broadcasting techniques described above may alsoallow for polling. For example, SSDP may allow a device to poll otherdevices on the network to determine what services those devices provide,and those devices may respond with messages similar to the broadcastmessages described above. In some implementations, lower-level protocolpolling may be used, such as internet control message protocol (ICMP)pings or address resolution protocol (ARP) pings.

Information from poll responses may be used to identify devices in thehouse. For example, poll responses may include data that may be used toidentify the device, such as text describing the device or anidentifier. Poll responses may also be used to determine the state ofthe device. For example, a lack of a response to a poll request mayindicate that the device is off, a response may indicate that the deviceis on, and information in the response may provide additionalinformation (e.g., a song that is being played).

FIG. 4C illustrates an example timeline of power monitor 150 learninginformation about another device by monitoring network data sent by thedevice to other devices. In some implementations, individual devicemonitoring may only be used with an explicit opt in by a user or may useonly a network packet header (and not the packet body) to avoidcollecting too much information or avoid collecting sensitiveinformation.

In FIG. 4C, a monitored device turns on at 430. At 431, 432, 433, and434, the monitored device transmits data over the network to anotherdevice, which may be a device different from power monitor 150. At 435,the monitored device turns off and it stops sending networktransmissions. Power monitor 150 may passively receive this network dataon the network, such as by passively receiving network packets.

Power monitor 150 may process the received data to determine informationabout the monitored device. Information in the received data may be usedto identify the device, such as text describing the device or anidentifier. The received data may also be used to determine the state ofthe device. For example, the fact that the device is transmitting dataindicates that the device is on, and if the device does not transmit anydata over a period of time, it may be determined that the device is off.

In some implementations, power monitor 150 may have information aboutpublicly available APIs for third-party devices and use these APIs todetermine whether such third-party devices are present in the house. Forexample, power monitor 150 may periodically send out a request using theNest thermostat API to determine if a Nest thermostat is present in thehouse. After it is determined that a Nest thermostat is in the house, itmay be polled more frequently to determine the state of the Nestthermostat or the state of the heating/cooling system. The APIs mayallow, for example, other devices to determine the temperature of thehouse, a desired temperature set by a user, or a state of the heatingsystem or cooling system (e.g., whether the furnace is currently activeor start and stop times of furnace activity). Querying a device with aspecialized API may allow power monitor 150 to determine the state ofthe device itself (e.g., the Nest thermostat) and other devices that areconnected to it (e.g., the furnace).

In some implementations, power monitor 150 may subscribe tonotifications transmitted by third-party devices, which are referred toherein as a notifying devices. A notifying device may be configured totransmit notifications to other devices (e.g., periodically or upon astate change) and allow other devices to sign up to receive thenotifications using an API. Power monitor 150 may determine that anotifying device is in the house and then subscribe to receivenotifications from the device. Power monitor 150 may transmit requeststo receive notifications from notifying devices without knowing that thenotifying devices are present, and where the notifying devices arepresent, be subscribed to receive notifications. Some notifying devicesmay have a pairing procedure that requires assistance of a user, andpower monitor 150 may be configured to receive input from a user toassist with the pairing process, such as receiving a user name andpassword to pair with the notifying device.

Other third-party devices may also provide information about devicesthey are connected to, such as a smart switch 340 (e.g., Phillips Hue orBelkin Wemo). A smart switch may have an API to allow other devices tointeract with it, and power monitor 150 may use this API to determine astate of the switch, and accordingly whether the device connected to thesmart switch is consuming power (e.g., the device is on, the device isoff, or a dimmer-type switch is at 40%).

In some implementations, power monitor 150 may receive information abouta device in the house via a server external to the house, such as athird-party server that operates in conjunction with a third-partydevice in the house. Power monitor 150 may operate in conjunction with apower monitor server, and the third-party device in the house mayoperate in conjunction with the third-party server. For example, a Nestthermostat may send information about the state of the thermostat or theheating/cooling system of the house to a server operated by Nest. Thethird-party server may allow a user to provide configuration informationto cause the third-party server to transmit information to the powermonitor server using, for an example, an API of the power monitor serveror the third-party server. For example, the Nest server may transmitinformation received from the Nest thermostat in the house to the powermonitor server, such as on a periodic basis or when a state of thethermostat changes (or the state of the heating/cooling system changes).In some implementations, the power monitor server may send requests tothe third-party server for information about the third-party deviceinstead of receiving notifications from the third-party server. In someimplementations, the third-party device may communicate directly withthe power monitor server, or power monitor 150 may communicate directlywith the third-party server.

In some implementations, information received in a network transmissionfrom a device may be used to obtain further information about thedevice. For example, network transmissions may include a uniqueidentifier, such as a media access control (MAC) address. A uniqueidentifier may be used to determine additional information about thedevice using a data store or repository of information about devicesthat use the unique identifier. A data store may provide informationabout the type, make and/or version of the device based in the uniqueidentifier. For example, for MAC addresses, blocks of continuous MACaddresses may be specific to a type of device (e.g., television),manufacturer, or a version of the device (e.g., a particular model of atelevision). In some implementations, a data store of MAC addressinformation may be available, such as through a third-party service, andinformation about the device may be obtained using the MAC address. Adata store of identifiers may be created, purchased, or accessed (e.g.,using a third-party server) to obtain information about the device fromthe identifier.

In some implementations, user devices, such as a smartphone, may be usedto determine information about devices in the house, and the smart phonemay relay this information to power monitor 150. For example, speaker370 (e.g., a portable Bluetooth speaker) may not have a networkconnection with network device 310 and may instead use another network,such as a Bluetooth network, to communicate with other devices. Speaker370 may be too far from power monitor 150 such that power monitor maynot be able to detect the network of speaker 370. A user device, such asphone 360, may be brought into the same room as speaker 370, and phone360 may be able to determine that speaker 370 is present and/or anoperating state of speaker 370 using a direct network connection. Phone360 may then relay information about the presence and/or operating stateof speaker 370 to power monitor 150 or to a server that works inconjunction with power monitor 150.

In some implementations, network models may be used to identify devicesor determine states of devices by processing network data. A networkmodel may include any appropriate mathematical models, such asclassifiers, neural networks, self-organizing maps, support vectormachines, decision trees, random forests, logistic regression, Bayesianmodels, linear and nonlinear regression, and Gaussian mixture models. Anetwork model may receive as input data obtained from networktransmissions and output identifications of devices or device statechanges with an optional score. For example, a network model couldreceive a broadcast message, information about poll responses receivedfrom the device (or lack thereof), or information about network datagenerated by that device. In some implementations, the network model mayreceive only headers of network transmissions or may receive all datafrom the network transmissions.

In some implementations, a network model may be used to identify adevice or determine a state of a device using messages broadcast by thedevice. For example, a device may transmit a certain number and/or typeof messages before it turns off and a different number and/or type ofmessages when going into a sleep mode. A first network model may becreated for describing expected messages when a device is about to turnoff and a second network model may be created for describing expectedmessages when a device is about to go into sleep mode. When receivingbroadcast messages from the device, the messages may be processed withboth network models to generate a score for each network model, and thestate transition may be determined by the highest scoring network model.

Network models may also be created to describe other aspects of thenetwork transmissions described above. For example, network models maybe created to describe how often a device responds to a poll request andan expected time delay between transmitting the poll request andreceiving the response. In another example, a network model may becreated that describes expected network transmissions of a device in aparticular state, and this network model may be applied when passivelymonitoring network transmissions of a device.

In some implementations, a rules-based approach may be used to identifydevices in the house or determine the states of devices. Power monitor150 (or a server operating in conjunction with the power monitor) mayhave rules that have been created for identifying types of devices,makes of devices, or versions of device; rules for determining statechanges of devices; and rules for determining other aspects of devices.Rules may be created for any of the techniques described above, such asprocessing broadcast messages from a device, polling a device, ormonitoring network data generated by a device.

Some rules may output a boolean value to indicate whether the conditionsof the rule are met or not. For example, a rule may be created todetermine whether the device that transmitted the network data is atelevision, and if the conditions of the rule are satisfied, it isdetermined that the device is a television. Some rules may output ascore, for example, on a scale of 1 to 100, to indicate a match betweenthe network data and the rule. For example, a rule may be created todetermine whether the device that transmitted the network data is atelevision, and a score produced by the rule may be used to make thedetermination, such as by comparing the score to a threshold orcombining the score with other scores as described herein.

Multiple rules may exist for making a determination. For example,multiple rules may exist for determining whether the device thattransmitted the network data is a television, and if any one of therules is satisfied, it may be determined that the device is atelevision.

Any data in a network transmission or data relating to a networktransmission may be use as input into a rule. For example, informationextracted from a network transmission (such as a network address, anidentifier, a header, a string) may be used as input into a rule.Information that is not in the network transmission but it is related tothe network transmission may also be used, such as a time that thenetwork transmission was received.

In some implementations, a rule may comprise one or more conditions thatneed to be satisfied for the rule to be met. For example, a conditionmay include any comparison of data, such as inequality, equality,greater than or less than. Rules may employ any combinations ofconditions, including but not limited to combinations using Booleanalgebra. Examples of rules include the following: a device thatbroadcasts Zerconf services including AFP, HTTP, and SSH is an Apple MacOS computer; structured data returned as part of a NetBIOS STATUS pollrequest provides a user-visible name of a host; a device with apreviously-unseen MAC address making a DHCP request is a new devicejoining the network for the first time; and the vendor of a device isdetermined using known MAC address vendor prefixes.

In some implementations, device fingerprinting techniques may be used toidentify devices on the network. Device fingerprints may be created forknown devices, such as a Mac computers, Windows computers, and Linuxcomputers, and possibly different operating system versions of each. Afingerprint may be created by sending multiple requests to each deviceusing, for example, different protocols and port numbers (e.g., using aprogram such as Nmap). The responses of each device may be recorded tocreate a fingerprint for each device. Any appropriate data may be usedwhen creating device fingerprints, such as the number and types ofnetwork protocols broadcast by the device, broadcast behavior, number orfrequency of different types of broadcasts, or parameters used fornetwork transmissions (e.g., a TCP window size).

For an unknown device in the house, similar requests may be sent to thatdevice and the responses may be used to create a fingerprint for theunknown device. The fingerprint for the unknown device may be comparedwith the fingerprints for the known devices to determine informationabout the unknown device. For example, if the fingerprint of the unknowndevice has a closest match with the fingerprint for a Mac laptop, thenthe unknown device may be identified as a Mac laptop. In someimplementations, address resolution protocol (ARP) may be used toidentify devices on the network and then each of the identified devicesmay be fingerprinted using the techniques described above.

Any of the techniques described above for identifying devices ordetermining device states using network data may generate a scoreindicating a match between the data and the identified device or statechange. For example, applying a rule to a broadcast message may resultin a determination that the device is a Toshiba television with a scoreof 80% or a Sony television with a score of 60%. The scores generated bynetwork models may be combined with scores generated by power models asdescribed in greater detail below.

Combined Power and Network Monitoring

FIG. 5 illustrates a system 500 for providing users with informationabout devices in their home using one or both of power monitoring andnetwork monitoring. In FIG. 5, power monitor 150 may have any of thefunctionality described above. For example, power monitor 150, mayidentify the existence of devices in the house, may determine states ofdevices in the house, and may determine power consumption of devices inthe house. Power monitor 150 may transmit the information about devicesin the home to servers 510 using any known networking techniques. Forexample, power monitor may have a wireless connection to a router, whichin turn connects to servers 510.

Servers 510 may process the information received from power monitor 150and present information to users, such as through user device 540.Servers 510 may maintain a device list for devices in the home andupdate the device list with newly identified devices or updated statesof devices. Servers 510 may further record a log of device statechanges, record a history of power consumption of the house andindividual devices, and perform any of the other operations described inU.S. Pat. No. 9,443,195. For performing some operations, servers 510 mayaccess other resources, such as third-party servers 530 and a deviceinformation data store 520.

A user may obtain information about devices in the house using userdevice 540. User device 540 may be any device that provides informationto a user including but not limited to phones, tablets, desktopcomputers, and wearable devices. User device 540 may present, forexample, information about device state changes and real-time powerusage to the user. For example, user device 540 may present a web pageto the user or a special-purpose app may be installed on user device540. The information presented by user device 540 may include any of theinformation described in U.S. Pat. No. 9,443,195.

To provide information to users about devices in a home, a list ofdevices in the home may be maintained. FIG. 6 illustrates an exampledevice list 600. The list of devices may include any informationrelating to devices in the home, including but not limited to a deviceID (which may be particular to the home or all devices known by acompany providing the service), a name (e.g., a user supplied name), atype, a make, a version, one or more power models that are used toidentify state changes of the device, a network ID (e.g., a networkaddress or other identifier, such as a MAC address), and one or morenetwork models that are used to identify state changes of the device,and a state of the device.

Device list 600 may be stored in one or more locations. For example,device list 600 may be stored at one or more of power monitor 150,servers 510, device information data store 520, or on user device 540.Different versions of the device list may be stored in differentlocations corresponding to the processing at the location. For example,power monitor 150 may not store the name, type, make, or version of thedevices because this information may not be needed to determine devicestate changes. User device 540 may not store information about powermodels and network models because user device 540 may not determine anydevice state changes.

FIG. 7 illustrates a system 700 with a power monitor 150 that processesa power monitoring signal and network data to identify devices in thehome and to identify state changes of devices in the home. As above,home 110 is supplied with power from electric company 120. An electricalpanel 140 receives the power and distributes the power to devices in thehome. Some devices receive power from electrical panel 140 and are notconnected to the network (e.g., refrigerator 160, stove 165, and lightbulb 350). Some devices receive power from electrical panel and areconnected to the network (e.g., power monitor 150, network device 310,smart television 320, computer 330, and smart switch 340). Some devicesmay be connected to the network but not receive power from electricalpanel 140 or only sometimes receive power from electrical panel (e.g.,phone 360 that may be charged with phone charger 710).

As above, power monitor 150 may receive one or more power monitoringsignals from sensor 130 that measures an electrical property of powerprovided to house 110. Power monitor 150 is also connected to thenetwork in house 110 via network device 310. Power monitor 150 mayreceive network data from other devices via network device 310 (asindicated by the dotted lines) or may receive network data directly fromother devices (not shown in FIG. 7). For some devices in the home,either one or both of power monitoring and network monitoring may beinaccurate or have higher error rates than desired when identifyingdevices or state changes of devices. By using both power monitoring andnetwork monitoring cooperatively or simultaneously, the performance ofidentifying devices or state changes of devices may be improved.Simultaneous power monitoring and network monitoring may be implementedusing any appropriate techniques, as described in greater detail below,such as combining scores, rules, or voting techniques.

In some implementations, the operations of power monitor 150 may changedepending on whether a user is interacting with user device 540 to viewinformation about devices in the house. Where a user is viewinginformation about devices in the home using user device 540, it may bedesired to identify new devices or state changes of devices more quicklythan when no users are viewing information about devices in the home.

When a user starts viewing information about devices in the home withuser device 540, user device 540 may establish a network connection toservers 510, and servers 510 may transmit information about devices touser device 540. Servers 510 may also have a network connection (eitherdirect or indirect) with power monitor 150. Accordingly, servers 510 maytransmit information to power monitor 150 to cause the operations ofpower monitor 150 to change. Any operations of power monitor 150 may bechanged to improve the user experience for the end user. In someimplementations, power monitor 150 may change its operations to identifynew devices and state changes of new devices more quickly. For example,power monitor may increase a polling frequency used to poll otherdevices in the house. Where no users are viewing information aboutdevices, a polling frequency of 5 minutes may be sufficient to determineupdates. When a user starts viewing information about devices, thepolling frequency may be increased (e.g., 10 seconds) to more quicklydetermine updates.

The arrangement and specific functions of the components of FIG. 5 andFIG. 7 provide just one example of how the techniques described hereinmay be implemented, but other configurations are possible. For example,power monitor 150 may perform some or all the operations of servers 510,and power monitor 150 may directly provide information to user device540. In another example, power monitor 150 may include some or all ofthe functionality of user device 540, and a user may interact directlywith power monitor 150 to obtain information about device events andpower consumption.

Identifying Devices

When power monitor 150 is first installed in a home, a device list maybe created for devices in the home. In some implementations, an emptydevice list may be created. In some implementations, a device list maybe initialized with devices based on input from one or more people inthe home. For example, a user may specify any of the types, makes,and/or versions of devices in the house.

Power monitor 150 may use one or both of power monitoring and networkmonitoring to add or update devices in the device list using any of thetechniques described herein. Devices may be added to the device listafter they are identified by power monitor, and devices on the devicelist may be further updated as additional information about them isdetermined. For example, power monitor 150 may initially determine thatthe house has a dishwasher, and it may later determine that the househas a Kenmore 1000 dishwasher.

In some implementations, power monitor 150 may add multiple devices tothe device list in response to processing a power event in the powermonitoring signal. For example, if two power models produce a scoreabove a threshold, then devices corresponding to each power model may beadded to the device list. In some implementations, the scores producedby the power models may be included in the device list as well.

Power monitor 150 may also process network data to identify devices inthe house and add them to the device list. For example, power monitor150 may use any of the techniques described above to obtain informationabout devices connected to a network in the house, and then add devicesto the device list for the house.

In some implementations, power monitor 150 may add multiple devices tothe device list (optionally with scores) in response to processing anetwork data transmission. For example, in response to processing abroadcast message, a Toshiba television may be added to the device listwith a first score and a Sony television may be added to the device listwith a second score.

Scores for devices on the device list may be updated over time. Forexample, processing a first power event may cause a first device and asecond device to be added to the device list with corresponding scores.At a later time, power monitor 150 may process a second power event togenerate a second set of scores for the first and second devices. Thesecond set of scores generated using the second power event may be usedto update the overall scores for the first and second devices on thedevice list.

Similarly, network data transmissions at later times may be used toupdate a score for a device on a device list. For example, a first andsecond device may be added to a device list with corresponding scoresbased on processing a first network transmission. At a later time, powermonitor 150 may process a second network transmission and generatesecond scores for the first and second devices. As above, the second setof scores generated using the second network transmission may be used toupdate the overall scores for the first and second devices on the devicelist.

In some implementations, a device on a device list may have a score thatis generated using both power monitoring and network monitoring. A firstdevice may be added to the device list with a corresponding score afterprocessing a power event. Later, the score for the first device may beupdated by processing a first network transmission. An overall score fora device on the device list may be generated by any combination ofprocessing power events and network transmission events.

Scores may be combined using any appropriate techniques. In someimplementations, an overall score for a device may be an average of allindividual scores generated for that device. In some implementations, avariance may be determined for each of the scores, and the scores may benormalized (e.g., Z-scored) before being combined.

In some implementations, power monitor may simultaneously use both powermonitor monitoring and network monitoring to identify devices. For adevice that is connected to the electrical line and has a networkconnection, the device may, around the time of a state change, cause apower event in the power monitoring signal and transmit data over thenetwork (a network event). Power monitor 150 may simultaneously processboth the power event and the network event to identify the device.

The power event and network event may appear in either order. FIG. 8Aillustrates an example where a power event 810 at a first time isfollowed by a network event 820 at a second time. For example, powerevent 810 may correspond to the television being turned on and networkevent 820 may correspond to a broadcast message by the televisionannouncing the availability of services. FIG. 8B illustrates an examplewhere a network event 850 at a first time is followed by a power event860 at a second time. For example, a user may turn off the televisionand network event 850 may be a broadcast message withdrawing servicesand power event 860 may correspond to the television turning off.

When processing a power event, power monitor 150 may look for networkevents that are temporally close to the power event (e.g., within a timeinterval, such as within 1 second) and process them simultaneously. Forexample, power monitor 150 may process network events where thedifference between the time of the power event and the time of thenetwork event is less than a threshold. Similarly, when processing anetwork event, power monitor 150 may look for power events that aretemporally close to network event.

In some implementations, power monitor 150 may process a power event andgenerate scores for corresponding power models. Power monitor 150 maythen look for network events that are temporally close to the powerevent and use information from the network event to adjust the scoresgenerated by the power models. For example, the top two scoring powermodels may be for a Toshiba television and a Sony television and thescores may be close to each other. A network event may occur shortlyafter the power event, and the network event may correspond to a Toshibatelevision. Power monitor 150 may use the network event may to increasethe score for identifying a Toshiba television and then identify aToshiba television and add it to the device list.

A time difference between a power event and a network event may also beused to identify devices. A device may send out a network event with aconsistent delay after causing a power event or vice versa. For example,a television turning on may consistently send out a network event (e.g.,broadcasting services) at about 3.5 seconds after causing a power event.The timing of the power events and network events may be a feature thatmay be used with any of the identification techniques described herein.

In some implementations, device identification models may be used thatreceive both information about a power event and information about anetwork event as input and then generate scores indicating a matchbetween the input and a device. For example, a device identificationmodel may be created for a type of device, a make of a device, or aversion of a device. In some implementations, power monitor 150 maycompute a score for each device identification model, select a deviceidentification model having a highest score, and identify the deviceusing the highest scoring device identification model. Deviceidentification models may be created using any appropriateclassification techniques, such as neural networks, self-organizingmaps, support vector machines, decision trees, random forests, logisticregression, Bayesian models, linear and nonlinear regression, andGaussian mixture models.

In some implementations, confidence levels may be computed in additionto scores, and the confidence levels may be used in determining whetherto add a device to the device list or update information about a devicein the device list. For example, where only one score is above athreshold and the score is much higher than all of the other scores,then the confidence level may be high. Where multiple scores are abovethe threshold, no scores are above the threshold, or the highest scoreis close to the second highest score, then the confidence may be low.Any appropriate techniques may be used to determine a confidence levelfor the highest scoring device state change. Where a highest scoringmodel (e.g., power model, network model, or device identification model)has a low confidence level, the device list may not be updated.

Devices may also be removed from the device list. For example, a usermay review the device list and remove devices that are not present inthe house. Devices may also be removed from the device listautomatically. For example, a device may be removed if it hasn't beenidentified for longer than a period of time, if an overall score for thedevice falls below a threshold, or sufficient data has been obtained todistinguish the device from alternative devices (e.g., enough data hasbeen collected to determine with confidence that the television is aToshiba television and not a Sony Television).

FIG. 9 is a flowchart illustrating an example implementation ofidentifying devices in a building. In FIG. 9, the ordering of the stepsis exemplary and other orders are possible, not all steps are requiredand, in some implementations, some steps may be omitted or other stepsmay be added. The process of the flowcharts may be implemented, forexample, by any of the computers or systems described herein.

At step 910, a power monitoring signal is obtained. For example, a powermonitoring signal may be obtained by receiving measurements from asensor that measures an electrical property of a power line in thebuilding, such as a current or voltage sensor. The power line may powersome or all of the devices in the building. The power monitoring signalmay also be obtained by receiving it from another device. For example, aserver may receive a power monitoring signal that is transmitted by apower monitor.

At step 920, the power monitoring signal is processed with a pluralityof models to generate a score for each of the models. Each model mayhave been created for identifying information about devices, such as atype of device, make of device, or version of device. Any appropriatemodels may be used, such as any of the models described herein. Thescores may be any value indicative of a match between the powermonitoring signal and the model, such as a likelihood or a loglikelihood. Processing the power monitoring signal with the models maybe performed by extracting features from the power monitoring signal andthen processing the features with the models.

At step 930, first information is determined about a first device in thebuilding using the scores. In some implementations, a highest scoringmodel may be selected and the first information may be associated withthe highest scoring model. For example, a highest scoring model mayindicate that the first device is a dishwasher, and the firstinformation may be that the device is a dishwasher. In someimplementations, information about network transmissions may be combinedwith the scores from the power models to determine the first informationabout the first device as described herein.

At step 940, a device list is updated with the first information aboutthe first device. The device list may be stored in any appropriatelocation, such as on the power monitor or on a server that operates inconjunction with the power monitor. Where the device list does not yetinclude any information about the first device, a new entry may be addedto the device list with the first information. Where the first device isalready on the device list, an entry for the first device may be updatedwith the first information. For example, where the first information isthat the first the device is a Kenmore dishwasher and the device listhas an entry for the first device as a dishwasher, the device list maybe updated to indicate that the make of the dishwasher is Kenmore. Powermonitor may cause the device list to be updated locally or cause thedevice list to be updated by transmitting the first information to aserver to cause the server to update the device list.

At step 950, a network data transmission is received from a seconddevice via a network in the building. The network data transmission maybe received directly from the second device (e.g., a point-to-pointBluetooth network) or indirectly from the second device (e.g., via anetwork router). The network data transmission may take any appropriateformat, such as a network packet or Ethernet packet. The network datatransmission may be received using any of the techniques describedherein, such as receiving a broadcast message in a broadcast networkpacket, receiving a response to a poll request, or monitoring networktransmissions on the network.

At step 960, second information about the second device is determinedusing the network data transmission. The second information may bedetermined using data or information in the network packet or otherinformation relating to the network data transmission, such as a time ofreceipt of the network transmission. In some implementations, the secondinformation may be determined using multiple network transmissions. Thesecond information about the second device may be determined using anyof the techniques described herein, such as processing informationrelating to the network data transmission with rules or network models.In some implementations, the information in or about the network datatransmission may be combined with information obtained from powermonitoring (e.g., scores from power models) to determine the secondinformation.

At step 970, the device list is updated with the second informationabout the second device, similar to step 940.

At step 980, a request is received for information about devices in thebuilding. For example, a user may use a user device, such as asmartphone or tablet, to view information about devices in the building.Software running on the user device (e.g., a web page viewed in abrowser or a special purpose app) may request information about devicesin the building and send a request, for example using a REST API. Therequest may be received be a server operating in conjunction with powermonitor.

At step 990, the first information and second information aretransmitted to the user device. For example, the first information maybe that the first device is a dishwasher and the second information maybe that the second device is a Toshiba television. The information maybe transmitted by a server operating in conjunction with the powermonitor and the information may be presented by software running on theuser device.

In some implementations, devices in a building may be identified asdescribed in the following clauses, combinations of any two or more ofthem, or in combination with other clauses presented herein.

1. A system for identifying devices in a building, the system comprisingat least one computer comprising at least one processor and at least onememory, the at least one computer configured to: obtain a powermonitoring signal by measuring an electrical property of a power line inthe building, wherein the power line provides power to the devices inthe building; process a first power event in the power monitoring signalwith a plurality of power models to generate a score for each powermodel of the plurality of power models, wherein the first power eventcorresponds to a state change of a first device; determine firstinformation about the first device using the scores; cause the firstdevice to be updated in a device list using the first information aboutthe first device; receive a first broadcast network packet, wherein thefirst broadcast network packet was sent by a second device; determine,using information in the first broadcast network packet, secondinformation about the second device; cause the second device to beupdated in the device list using the second information about the seconddevice; receive a request for information about devices in the buildingfrom a user device; and transmit the first information about the firstdevice and the second information about the second device to the userdevice.

2. The system of clause 1, wherein the first information about the firstdevice comprises a type of the first device, a make of the first device,or a version of the first device.

3. The system of clause 1, wherein the at least one computer isconfigured to receive a second broadcast network packet, wherein thesecond broadcast network packet was sent by the first device; anddetermine the first information about the first device using theplurality of scores and information in the second broadcast networkpacket.

4. The system of clause 3, wherein a type of the first device isdetermined using the plurality of scores and a make of the first deviceis determined using the information in the second broadcast networkpacket.

5. The system of clause 3, wherein the first power event in the powermonitoring signal occurs before receiving the second broadcast networkpacket.

6. The system of clause 3, wherein the at least one computer isconfigured to select the second broadcast network packet by comparing atime of the first power event and a time of the second broadcast networkpacket.

7. The system of clause 1, wherein the at least one computer comprises apower monitor installed in the building and a server computer with anetwork connection to the power monitor.

8. The system of clause 1, wherein the information in the firstbroadcast network packet comprises an identifier of the second deviceand wherein the at least one computer is configured to obtain the secondinformation about the second device from a data store using theidentifier of the second device.

9. The system of clause 1, wherein the at least one computer isconfigured to determine second information about the second device byprocessing the information in the first broadcast network packet with aplurality of rules, wherein each rule of the plurality of rulescomprises comparing information in the network packet to at least onecondition.

10. A computer-implemented method for identifying devices in a building,the method comprising: obtaining a power monitoring signal by measuringan electrical property of a power line in the building, wherein thepower line provides power to the devices in the building; processing afirst power event in the power monitoring signal with a plurality ofpower models to generate a score for each power model of the pluralityof power models, wherein the first power event corresponds to a statechange of a first device; determining first information about the firstdevice using the scores; causing the first device to be updated in adevice list using the first information about the first device;receiving a first broadcast network packet, wherein the first broadcastnetwork packet was sent by a second device; determining, usinginformation in the first broadcast network packet, second informationabout the second device; and causing the second device to be updated inthe device list using the second information about the second device.

11. The computer-implemented method of clause 10, wherein the powermonitoring signal indicates a current or voltage of the power line.

12. The computer-implemented method of clause 10, comprising receiving aplurality of broadcast network packets, wherein each of the plurality ofbroadcast network packets was sent by the first device; and determiningthe first information about the first device using the plurality ofscores and information in the plurality of broadcast network packets.

13. The computer-implemented method of clause 10, wherein determiningthe second information about the second device comprises processing theinformation in the first broadcast network packet with a plurality ofnetwork models to generate a second score for each network model of theplurality of network models; and determining the second informationabout the second device using the second scores for the plurality ofnetwork models.

14. The computer-implemented method of clause 10, wherein determiningthe second information about the second device comprises generating asecond score for each identification model of a plurality ofidentification models, wherein each identification model processes asecond power event in the power monitoring signal and the information inthe first broadcast network packet; and determining the secondinformation about the second device using the second scores for theplurality of identification models.

15. The computer-implemented method of clause 10, comprising receiving aplurality of broadcast network packets, wherein each broadcast networkpacket of the plurality of broadcast network packets was sent by thesecond device; and determining the second information about the seconddevice using the information in the plurality of broadcast networkpackets.

16. The computer-implemented method of clause 15, wherein determiningthe second information comprises using a first time corresponding to afirst broadcast network packet and a second time corresponding to asecond broadcast network packet.

17. One or more non-transitory computer-readable media comprisingcomputer executable instructions that, when executed, cause at least oneprocessor to perform actions comprising: obtaining a power monitoringsignal by measuring an electrical property of a power line in thebuilding, wherein the power line provides power to the devices in thebuilding; processing a first power event in the power monitoring signalwith a plurality of power models to generate a score for each powermodel of the plurality of power models, wherein the first power eventcorresponds to a state change of a first device; determining firstinformation about the first device using the scores; causing the firstdevice to be updated in a device list using the first information aboutthe first device; receiving a first broadcast network packet, whereinthe first broadcast network packet was sent by a second device;determining, using information in the first broadcast network packet,second information about the second device; and causing the seconddevice to be updated in the device list using the second informationabout the second device.

18. The one or more non-transitory computer-readable media of clause 17,wherein determining the first information about the first devicecomprises selecting a highest scoring power model using the plurality ofscores and wherein the first information corresponds to the highestscoring power model.

19. The one or more non-transitory computer-readable media of clause 17,wherein the second information about the second device comprises a typeof the second device, a make of the second device, or a version of thesecond device.

20. The one or more non-transitory computer-readable media of clause 17,wherein the at least one computer is configured to determine secondinformation about the second device by processing the information in thefirst broadcast network packet with a plurality of rules.

The techniques described above use a combination of power monitoring andnetwork monitoring to provide improved identification of devices in abuilding over techniques based on only power monitoring. With only powermonitoring, some devices may not be able to be identified at all or maybe identified but with a lower accuracy. The combination of networkmonitoring with power monitoring allows a greater number of devices tobe identified (such as networked devices without mechanical components)and devices may also be identified with greater accuracy. Usinginformation from both power monitoring and network monitoring allows forthe creation of models and/or classifiers with a lower error rate thanmodels and/or classifiers that use only information from powermonitoring.

Identifying Device State Changes

In addition to identifying devices in the house, power monitor 150 mayalso determine the states of devices in the house using one or both ofpower monitoring and network monitoring. Some devices (e.g., lightbulbs) may only have two states, on and off. Other devices may havemultiple states. For example, a clothes washer may have a wash cycle, arinse cycle, and a spin cycle. A television may have an on state, an offstate, and a sleep state.

Power monitoring may be used to identify state changes using any of thetechniques described herein and in U.S. Pat. No. 9,443,195. For example,power monitor 150 may process the power monitoring signal, select apower model that produced a highest score, determine the device statechange from the model, and update the state of the device in the devicelist.

Network monitoring may also be used to identify state changes using anyof the techniques described herein. For example, power monitor mayprocess broadcast messages, poll devices, and monitor device networkdata to determine the states of devices from their network data asdescribed above.

In some implementations, power monitor may simultaneously use both powermonitor monitoring and network monitoring to identify device statechanges. For a device that is connected to both the electrical line anda network connection, the device may, around the time of a state change,cause a power event in the power monitoring signal and transmit dataover the network (a network event). Power monitor may process both thepower event and the network event to identify the state change. Thepower event and network event may appear in either order as describedabove.

As above, when processing a power event, power monitor may look fornetwork events that are temporally close to the power event and processthem simultaneously. For example, power monitor may process networkevents where the difference between the time of the power event and thetime of the network event is less than a threshold. Similarly, whenprocessing a network event, power monitor may look for power events thatare temporally close to network event.

In some implementations, power monitor may process a power event andgenerate scores for corresponding power models. Power monitor may thenlook for network events that are temporally close to the power event anduse information from the network event to adjust the scores generated bythe power models. For example, the top two scoring power models may be aToshiba television turning on and a computer turning on and the scoresmay be close to each other. A network event may occur shortly after thepower event, and the network event may correspond to a Toshibatelevision turning on. Power monitor may use the network event may toincrease the score for the Toshiba television turning on. For example,the score may be increased by a fixed amount, a percentage, or may becombined with a score generated by the network event processing togenerate an overall score for the device state change. Power monitor maythen identify the state change as corresponding to the Toshibatelevision turning on. The timing of power events and network events mayalso be used as a feature for any of the techniques described herein fordetermining device state changes.

For some devices, the timing between a device state change and networkevents may not be precisely known. For example, in some implementations,it may be determined that a device is off when the device has nottransmitted any network data for a period of time. It may thus bedetermined that the device turned off sometime after its last networktransmission, but the time it was turned off may not be known. In someimplementations, power monitor may process network events to determine atime varying score. For example, where a device's last networktransmission was at a first time, power monitor may output a higherscore for the time period shortly after the first time and a lower scorefor later times, such as a score with an exponential decay.

Some devices may have a known rebroadcast window, where the device willrebroadcast at set time intervals the services provided by the device.Where the device has send out a broadcast, but has not sent out anotherbroadcast within the rebroadcast window, it may be determined that thedevice has been turned off.

In some implementations, state change models may be used that receiveboth information about a power event and information about a networkevent as input and then generate scores indicating a match between theinput and a device state change. For example, a state change model maybe created for each state change of a device (e.g., state changes for atype of device, a make of a device, or a version of a device). In someimplementations, power monitor may compute a score for each state changemodel, select a state change model having a highest score, and identifythe state change using the highest scoring state change model. Statechange models may be created using any appropriate classificationtechniques, such as neural networks, self-organizing maps, supportvector machines, decision trees, random forests, logistic regression,Bayesian models, linear and nonlinear regression, and Gaussian mixturemodels.

As above, confidence levels may be computed in addition to scores, andthe confidence levels may be used in determining whether a state changehas occurred. Where a highest scoring model (e.g., power model, networkmodel, or state change model) has a low confidence level, the statechange may not be identified.

In determining device state changes, power monitor 150 may use a list ofknown states of devices and possible transitions between the states ofdevices. For example, a television may have three states: an on state,an off state, and a sleep state.

Because of how the television operates, however, not all statetransitions may be possible. For the three states, there are sixpossible state transitions (on to off, on to sleep, off to on, off tosleep, sleep to on, and sleep to off). From the “off” state, it may onlybe possible to transition to the “on” state (off to sleep is notpossible). From the “sleep” state, it may only be possible to transitionto the “on” state (sleep to off is not possible). Accordingly, powermonitor may implement techniques (e.g., models or rules) for recognizingall of the possible state changes of devices. When determining a statechange of a device, power monitor may select a state change from a listof possible state changes of the device, and the current state may bedetermined from the ending state of the state change (e.g., whenselecting an off to on state change, it is determined that the device isnow on). When determining a state of a device, power monitor may selecta state from a list of possible states of the device. Power monitor mayselect state changes or states depending on the implementation and/orthe device being monitored.

Any of the techniques described above for identifying devices may alsobe used for determining state changes of devices. Similarly, any of thetechniques described for determining state changes of devices may alsobe used to identify devices.

FIG. 10 is a flowchart illustrating an example implementation ofdetermining states of devices. In FIG. 10, the ordering of the steps isexemplary and other orders are possible, not all steps are required and,in some implementations, some steps may be omitted or other steps may beadded. The process of the flowcharts may be implemented, for example, byany of the computers or systems described herein.

At step 1010, information about devices in a building is accessed from adata store. The information may be stored in any suitable way and storedin any suitable location or multiple locations. For example, powermonitor 150 may obtain information about devices in the building from alocally stored device list that includes information about techniquesfor determining device state changes (e.g., information about models orrules). Power monitor may also access information from a device liststored on a server. The stored information may include information aboutdevices powered by a power line in the building and/or connected tonetwork in the building.

At step 1020, a power monitoring signal is obtained, similar to step910.

At step 1030, a state of the first device is determined using the powermonitoring signal. Any of the techniques described herein may be used todetermine the state of the first device, such as computing a pluralityof scores using a plurality of power models and selecting a state orstate change corresponding to a highest scoring power model. The stateor state change of the first device may be selected from a list ofpossible states or state changes of the first device. In someimplementations, network monitoring techniques may not be used todetermine the state (even if the first device has a network connection).In some implementations, power monitoring techniques may be combinedwith network monitoring techniques to determine the state of the firstdevice, for example by using any of the techniques described herein. Insome implementations, the state of the first device may be determined byfirst determining a state change and then determining the state of thefirst device from the state change.

At step 1040, the state of the first device is updated in the storedinformation. Any of the techniques described in step 940 for updating adevice list may also be used to update the state of the first device ina device list. For example, power monitor may cause the state to beupdated in a locally stored device list or transmit information to aserver to cause the server to update a device list with the state of thefirst device.

At step 1050, a network data transmission is received. Any of thetechniques described in step 950 may be used to receive a networktransmission. In some implementations, a power monitor server operatingin conjunction with a power monitor may receive a network datatransmission from another server operating in conjunction with a devicein the house (e.g., a Nest server operating in conjunction with a Nestthermostat), a power monitor may receive a network data transmissiondirectly from a server operating in conjunction with a device in thehouse, or a power monitor server may receive a network transmissiondirectly from a device in the house.

At step 1060, it is determined that a second device transmitted thenetwork data. Any appropriate techniques may be used to determine thatthe second device transmitted the network data, such as using a networkaddress or identifier in the network data to identify the second deviceas the sender of the network data. Where a power monitor receivesnetwork data from the second device via another device, such as arouter, the second device may still be considered the sender ortransmitter of the network data. Where the network data transmission isreceived via another server, it may be determined that the network datatransmission corresponds to the second device rather than beingtransmitted by the second device.

At step 1070, a state of the second device is determined using thenetwork data. Any of the techniques described herein may be used todetermine the state of the second device using the network data. Thestate or state change of the second device may be selected from a listof possible states or state changes of the second device. In someimplementations, power monitoring techniques may not be used todetermine the state (even if the second device receives power from apower line in the building). In some implementations, network monitoringtechniques may be combined with power monitoring techniques to determinethe state of the second device, for example by using any of thetechniques described herein. In some implementations, the state of thesecond device may be determined by first determining a state change andthen determining the state of the second device from the state change.

At step 1080, the state of the second device is updated in the storedinformation. Any of the techniques described in steps 940 or 1040 forupdating a device list may also be used to update the state of thesecond device in a device list.

At step 1090, a request for information about devices in the building isreceived. Any of the techniques described in step 980 may be used torequest information about devices in the building.

At step 1095, information about the state of the first device and thestate of the second device is transmitted to the user device. Forexample, information may be transmitted to the user device to indicatethat the first device is off and the that the second device is in asleep state.

In some implementations, states of devices may be determined asdescribed in the following clauses, combinations of any two or more ofthem, or in combination with other clauses presented herein.

1. A computer-implemented method for determining states of devices in abuilding, the method comprising: accessing stored information aboutdevices in the building, wherein the devices in the building comprise afirst device and a second device, and wherein the information about thedevices comprises a state of the first device and a state of the seconddevice; obtaining a power monitoring signal by measuring an electricalproperty of a power line in the building, wherein the power lineprovides power to the devices in the building; determining the state ofthe first device by (1) processing a first power event in the powermonitoring signal with a plurality of power models to generate a scorefor each power model of the plurality of power models, and (2) selectinga state of the first device from a plurality of possible states usingthe scores; causing the state of the first device to be updated in thestored information using the selected state; receiving a first broadcastnetwork packet, wherein the first broadcast network was transmitted bythe second device; determining, using the information in the firstbroadcast network packet, that the first broadcast network packet wassent by the second device; selecting, using the information in the firstbroadcast network packet, the state of the second device from aplurality of possible states for the second device; and causing thestate of the second device to be updated in the stored information usingthe selected state.

2. The computer-implemented method of clause 1, wherein the firstbroadcast network packet comprises a broadcast using simple servicediscovery protocol, zero-configuration networking, or NetBIOS.

3. The computer-implemented method of clause 1, the method comprisingtransmitting a request for information to the second device; and whereinreceiving the first broadcast network packet comprises receiving aresponse to the request for information.

4. The computer-implemented method of clause 3, wherein transmitting therequest for information comprises polling the second device, requestinginformation using an API of the second device, or requesting informationabout services provided by the second device.

5. The computer-implemented method of clause 1, wherein selecting thestate of the second device comprises (1) processing the information inthe first broadcast network packet with a plurality of network models,and (2) selecting a highest scoring network model, wherein the highestscoring network model corresponds to the selected state.

6. The computer-implemented method of clause 1, wherein selecting thestate of the second device comprises processing the information in thefirst broadcast network packet with a plurality of rules, wherein eachrule of the plurality of rules comprises comparing information in thenetwork packet to at least one condition.

7. The computer-implemented method of clause 1, wherein select the stateof the second device comprises: processing a second power event in thepower monitoring signal with the plurality of power models to generate asecond score for each power model of the plurality of power models;processing the information about the first broadcast network packet witha plurality of network models to generate a third score for each networkmodel of the plurality of network models; and selecting the state usingthe second scores and the third scores.

8. The computer-implemented method of clause 1, wherein selecting thestate of the second device comprises generating a second score for eachstate change model of a plurality of state change models, wherein eachstate change model processes a second power event in the powermonitoring signal and the information in the first broadcast networkpacket; and selecting the state using the second scores.

9. The computer-implemented method of clause 1, comprising receiving aplurality of broadcast network packets, wherein each broadcast networkpacket of the plurality of broadcast network packets was transmitted bythe second device; and selecting the state of the second device usinginformation in the plurality of broadcast network packets.

10. A system for determining states of devices in a building, the systemcomprising at least one computer comprising at least one processor andat least one memory, the at least one computer configured to: storeinformation about devices in the building, wherein the devices in thebuilding comprise a first device and a second device, and wherein theinformation about the devices comprises a state of the first device anda state of the second device; obtain a power monitoring signal bymeasuring an electrical property of a power line in the building,wherein the power line provides power to the devices in the building;determine a state of the first device by (1) processing a first powerevent the power monitoring signal with a plurality of power models togenerate a score for each power model of the plurality of power models,and (2) selecting a state of the first device from a plurality ofpossible states using the scores; cause the state of the first device tobe updated in the stored information using the selected state; receivefirst network data from a server computer, wherein the server computertransmitted the network data based on information received from thesecond device; determine, using the first network data, that the firstnetwork data corresponds to the second device; select, using the firstnetwork data, a state of the second device from a plurality of possiblestates for the second device; and cause the state of the second deviceto be updated in the stored information using the selected state.

11. The system of clause 10, wherein the at least one computer isconfigured to cause the state of the first device to be updated in thestored information by transmitting the state of the first device to aserver computer.

12. The system of clause 10, wherein the power monitoring signalindicates a current or voltage of the power line.

13. The system of clause 10, wherein the at least one computer comprisesa power monitor installed in the building and a server computer with anetwork connection to the power monitor.

14. The system of clause 13, wherein the server computer is configuredto determine that a user device has a network connection with the servercomputer; the server computer is configured to send an indication to thepower monitor that the user device has a network connection with theserver computer; and the power monitor is configured to modify itsprocessing in response to receiving the indication.

15. The system of clause 14, wherein the power monitor is configured tomodify its processing by changing a frequency of polling devices.

16. The system of clause 10, wherein the at least one computer isconfigured to select the state of the second device by processing asecond power event in the power monitoring signal with the plurality ofpower models to generate a second score for each power model of theplurality of power models; and selecting the state using the secondscores and the information in the first network data.

17. The system of clause 10, wherein the at least one computer isconfigured to obtain information about power consumption of the seconddevice from a data store of device information using the state of thesecond device; and transmit the information about power consumption ofthe second device to a user device.

18. The system of clause 10, wherein the at least one computer isconfigured to transmit the state of the first device and the state ofthe second device to a user device.

19. One or more non-transitory computer-readable media comprisingcomputer executable instructions that, when executed, cause at least oneprocessor to perform actions comprising: obtaining a power monitoringsignal by measuring an electrical property of a power line in thebuilding, wherein the power line provides power to the devices in thebuilding; determining a state of a first device by (1) processing afirst power event in the power monitoring signal with a plurality ofpower models to generate a score for each power model of the pluralityof power models, and (2) selecting a state of the first device from aplurality of possible states using the scores; causing the state of thefirst device to be updated in a list of devices using the selectedstate; receiving a first broadcast network packet, wherein the firstbroadcast network packet was transmitted by a second device;determining, using information in the first broadcast network packet,that the first broadcast network packet was transmitted by the seconddevice; selecting, using the information in the first network event, astate of the second device from a plurality of possible states for thesecond device; and causing the state of the second device to be updatedin the list of devices using the selected state.

20. The one or more non-transitory computer-readable media of clause 19,wherein causing the state of the first device to be updated in thestored information comprises changing the state from an off state to anon state.

21. The one or more non-transitory computer-readable media of clause 19,wherein the plurality of power models comprises one or more of a devicemodel, a transition model, or a wattage model.

22. The one or more non-transitory computer-readable media of clause 19,wherein determining that the first broadcast network packet wastransmitted by the second device comprises using a network address oridentifier in the first broadcast network packet.

23. The one or more non-transitory computer-readable media of clause 19,wherein processing a first power event in the power monitoring signalwith a plurality of power models comprises computing a plurality offeatures using a portion of the power monitoring signal comprising thefirst power event; and processing the plurality of features with theplurality of power models.

The techniques described above use a combination of power monitoring andnetwork monitoring to provide improved identification of device statechanges in a building over techniques based on only power monitoring.With only power monitoring, some device state changes may not be able tobe identified at all or may be identified but with a lower accuracy. Thecombination of network monitoring with power monitoring allows a greaternumber of device state changes to be identified (such as state changesof networked devices without mechanical components) and device statechanges may also be identified with greater accuracy. Using informationfrom both power monitoring and network monitoring allows for thecreation of models and/or classifiers with a lower error rate thanmodels and/or classifiers that use only information from powermonitoring.

Reporting Power Usage

In some implementations, power monitor may provide users withinformation about the power consumption of individual devices in thehouse. For example, for any device where device state changes aredetermined using power monitoring and/or network monitoring, techniquesdescribed in U.S. Pat. No. 9,443,195 may be used to determine powerconsumption over time for the devices and/or present real-timeinformation about the power consumption of the devices to user.

Some devices in the house may have relatively constant power usage foreach state of the device or a power usage that falls within a range. Forexample, televisions and light bulbs may consume a relatively fixedamount of power when they are on and no power when they are off. Forsuch devices, an expected power consumption or power range may bedetermined by measuring the power usage of several examples of thedevices in each state and computing an average power consumption for thestate. A list of expected power usage or power range of the devices maybe created for each state and may be available to the power monitor.

When it is determined that a device with relatively constant power usageis in a particular state (e.g., by processing network events), powermonitor (or servers operating in conjunction with the power monitor) mayobtain an expected power usage or power range for the device state(e.g., from its own storage or a third-party server) and report to theuser that the device is consuming the expected amount of power or powerwithin a range. When the device turns off, power monitor may report tothe user that the device has stopped consuming power.

Some devices in the house may be “always on.” For example, cable modems,wireless routers, smart thermostats, and Internet-of-things devices maybe always on. For always on devices, an expected power usage or powerrange may be determined as described above. After an always on device isidentified as being in the house, power monitor may report to the userthat the device is always on and provide an expected power usage orpower range.

Power monitor (or servers operating in conjunction with the powermonitor) may also compute a total amount of energy consumed by deviceswith relatively constant power usage or devices that are always on. Forthese devices, a total amount of energy consumed by the device may becalculated by (1) determining the amount of time that the device hasbeen in each of its possible states, (2) determining an expected powerusage in each state, (3) determining a total amount of energy consumedin each state by multiplying the amount of time in a state by theexpected power consumption for the state, and (4) determining the totalamount of energy consumed by the device by adding the energy consumptionof each of the states.

Training Power Models using Network Events

Training power models for some devices may be more challenging than forother devices. Devices with mechanical components, such as pumps andmotors, may have power signatures that are easier to identify because ofthe relationship between the operation of the mechanical components andpower usage. Devices with few or without any mechanical components mayhave power signatures that are more difficult to identify. For example,many electronic devices, such as computers and televisions, may convertalternating current to direct current and then use the direct current topower internal electronics.

Power models may be trained using a training corpus of data as describedin U.S. Pat. No. 9,443,195. For example, tens, hundreds, or thousands ofexamples of a power event in a power signal corresponding to atelevision being turned on may be used to train a power model for thetelevision turning on. Because the power event corresponding to atelevision turning on may be similar to power events for otherelectronic devices turning on, it may be challenging to collectsufficient training data for all the electronic devices in the house.

Network events may be used to assist with collecting training data fortraining power models for devices that are connected to both the powerline and the network. Suppose that it is desired to train a power modelfor a first device (e.g., a television) turning on. Instances of thefirst device turning on may be identified by processing network eventsusing any of the techniques described above. Then, a portion of thepower monitoring signal corresponding to the first device turning on isstored so that it may later be used for training purposes. The portionof the power monitoring signal may include portions before and/or afterthe network event. By performing these steps over an extended period oftime and/or for multiple homes, a training corpus of training data maybe collected for training a power model for the first device turning on.

Any portion of a power monitoring signal may include multiple powerevents that are close to one another or even overlapping with oneanother. Accordingly, the collected training data may include powerevents for other device state changes in addition to power events forthe first device turning on. The power events for other devices may bereferred to as extraneous power events.

Different approaches may be used for handling the extraneous powerevents in the training data. In some implementations, no special actionsmay be taken and the power model may be trained using all of the data asit is. Although the training data will include the extraneous powerevents, if they are small in number as compared to power eventscorresponding to the first device turning on, it may not significantlyimpact the model training. In some implementations, training data withmore than one power event may discarded so that the power model for thefirst device is trained using only power monitor signal portionscontaining a single power event. In some implementations, the extraneouspower events may be identified so that only power events that are likelyto correspond to the first device turning on are used to train the powermodel. For example, features may be computed for all of the power eventsin the training data and clustering techniques (e.g., k-means) may beused to identify the extraneous power events. Where a portion of thepower monitoring signal contains a power event for the first deviceturning on at a first time and an extraneous power event at a secondtime, the power event for the first device turning on may be trainedusing only a portion of the power monitoring signal that includes thepower event at the first time.

A power model for the first device turning on may then be trained usingthe training data. Any appropriate techniques may be used for trainingthe power model, such as any of the techniques described in U.S. Pat.No. 9,443,195. For example, a power model may include any of atransition model, a device model, or a wattage model. Trainingtechniques may include, but are not limited to, training neuralnetworks, self-organizing maps, support vector machines, decision trees,random forests, logistic regression, Bayesian models, linear andnonlinear regression, and Gaussian mixture models.

Power models may also similarly be trained for other state changes ofthe first device and state changes of other devices.

FIG. 11 is a flowchart illustrating an example implementation of usingnetwork data to train a power model for a device. In FIG. 11, theordering of the steps is exemplary and other orders are possible, notall steps are required and, in some implementations, some steps may beomitted or other steps may be added. The process of the flowcharts maybe implemented, for example, by any of the computers or systemsdescribed herein.

At step 1110, information about a first network event in a building isreceived. A network event may correspond to any transmission of data,such as a network packet transmitted from a device in the building to apower monitor in the building. In some implementations, a server mayreceive the information about the network event from a power monitorwhere the power monitor received a network data transmission fromanother device in the building. The information about the network eventmay include information in the transmitted network data or informationabout the transmitted network data, such as a time of receipt. Thenetwork event may be associated with a time, such as a time of receiptof the network data by the power monitor.

At step 1120, it is determined that a first device changed state usingthe information about the network event. Any of the techniques describedherein may be used to determine that the first device state changedstate using the network event. The determination may be performed by apower monitor or by a server operating in conjunction with the powermonitor. In some implementations, other steps in the process may becontingent upon determining that the first device changed state. Forexample, a power monitor may process information about the network eventto determine that the first device changed state and only transmit theinformation about the network event and/or the power monitoring signal(in step 1130) after determining that the first device changed state.

At step 1130, a power monitoring signal is received, where the receivedpower monitoring signal is a portion of a power monitoring signal usedby a power monitor. For example, a server may receive the powermonitoring signal from the power monitor. The received power monitoringsignal may include a measurement taken at a time corresponding to thenetwork event (e.g., a time of transmission or receipt).

Steps 1110, 1120, and 1130 may be repeated any number of times, andcorresponding network events and power monitoring signals may be fromthe same building or may be from multiple buildings. The collected powermonitoring signals may correspond to devices sharing a common feature.For example, the power monitoring signals may all be from televisions,may all be from Toshiba televisions, or may be from a particular versionof a Toshiba television. Because the power monitoring signals share acommon feature, they may be used to train a power model to detect thatcommon feature. At step 1140, it may be determined whether additionaldata is available or desired for training a power model. If more data isavailable or desired, then processing may proceed to step 1110. If moredata is not available or desired, then processing may proceed to step1150.

At step 1150, a power model is trained using the power monitoringsignals received at one or more instances of step 1130. The power modelmay be any of the power models described herein or in U.S. Pat. No.9,443,195 and may be trained using any of the techniques describedherein or in U.S. Pat. No. 9,443,195. In some implementations, the powermonitoring signals may be processed to identify and remove or ignoreextraneous power events corresponding to devices other than the firstdevice, as described herein.

At step 1160, the trained power model may be deployed to a power monitorin a building. For example, the power model may be used by the powermonitor to identify devices in the building or identify device statechanges in the building using any of the techniques described herein.

In some implementations, power models may be trained as described in thefollowing clauses, combinations of any two or more of them, or incombination with other clauses presented herein.

1. A system for training a power model for identifying devices or devicestate changes, the system comprising at least one computer comprising atleast one processor and at least one memory, the at least one computerconfigured to: receive information about a first network event, whereinthe first network event corresponds to a first device in a firstbuilding transmitting data at a first time; determine that the firstdevice changed state using the information about the first networkevent; obtain a first power monitoring signal, wherein the first powermonitoring signal corresponds to a measurement an electrical property ofa power line in the first building, and wherein the first powermonitoring signal includes a measurement at the first time; receiveinformation about a second network event, wherein the second networkevent corresponds to a second device in a second building transmittingdata at a second time; determine that the second device changed stateusing the information about the second network event; obtain a secondpower monitoring signal, wherein the second power monitoring signalcorresponds to a measurement an electrical property of a power line inthe second building, and wherein the second power monitoring signalincludes a measurement at the second time; train a power model using thefirst power monitoring signal and the second power monitoring signal,wherein the power model is configured to identify a device or a statechange of a device using a power monitoring signal; and transmit thepower model to a power monitor in a third building.

2. The system of clause 1, wherein the first device and the seconddevice are the same type of device, have the same manufacturer, or havethe same version.

3. The system of clause 1, wherein the at least one computer comprises afirst power monitor in the first building, a second power monitor in thesecond building, and a server computer.

4. The system of clause 1, wherein the at least one computer isconfigured to obtain a third power monitoring signal, wherein the thirdpower monitoring signal corresponds to a measurement an electricalproperty of a power line in the third building; and process the thirdpower monitoring signal with the power model to determine that a thirddevice changed state.

5. The system of clause 1, wherein the at least one computer isconfigured to transmit a request for information to the second device;and wherein network data is received in response to the request forinformation.

6. The system of clause 1, wherein the at least one computer isconfigured to receive information about a plurality of network events,wherein each network event corresponds to the first device transmittingdata; and determine that the first device changed state using theinformation about the plurality of network events.

7. The system of clause 1, wherein the at least one computer isconfigured to determine that the first device changed state by (1)processing the information about the first network event with aplurality of network models, and (2) selecting a highest scoring networkmodel.

8. A method for training a power model for identifying devices or devicestate changes, the method comprising: receiving information about afirst network event, wherein the first network event corresponds to afirst device transmitting data at a first time; obtaining a first powermonitoring signal, wherein the first power monitoring signal correspondsto a measurement an electrical property of a power line, and wherein thefirst power monitoring signal includes a measurement at the first time;receiving information about a second network event, wherein the secondnetwork event corresponds to the first device transmitting data at asecond time; obtaining a second power monitoring signal, wherein thesecond power monitoring signal corresponds to a measurement anelectrical property of the power line, and wherein the second powermonitoring signal includes a measurement at the second time; training apower model using the first power monitoring signal and the second powermonitoring signal, wherein the power model is configured to identify thefirst device or a state change of the first device using a powermonitoring signal.

9. The method of clause 8, comprising determining that the first devicechanged state using the information about the first network event; anddetermining that the second device changed state using the informationabout the second network event.

10. The method of clause 8, comprising transmitting the power model to apower monitor in a building.

11. The method of clause 8, wherein the first network event comprises abroadcast network packet.

12. The method of clause 8, wherein the information about the firstnetwork event comprises a time of the first network event.

13. The method of clause 8, comprising determining that the first powermonitoring signal comprises a first power event and a second powerevent; determining that the first power event corresponds to the firstdevice changing state; and training the power model using the firstpower event.

14. The method of clause 13, wherein determining that the first powerevent corresponds to the first device comprises computing first featuresfor the first power event and second features for the second powerevent; and processing the first features and the second features with amathematical model or clustering the first features and second features.

15. The method of clause 13, wherein the first device is in a firstbuilding and the method comprising receiving information about a thirdnetwork event, wherein the third network event corresponds to a seconddevice in a second building transmitting data at a third time; obtaininga third power monitoring signal, wherein the third power monitoringsignal corresponds to a measurement an electrical property of a powerline in the second building, and wherein the second power monitoringsignal includes a measurement at the third time; and training the powermodel using the third power monitoring signal.

16. One or more non-transitory computer-readable media comprisingcomputer executable instructions that, when executed, cause at least oneprocessor to perform actions comprising: receiving information about afirst network event, wherein the first network event corresponds to afirst device transmitting data at a first time; obtaining a first powermonitoring signal, wherein the first power monitoring signal correspondsto a measurement an electrical property of a power line, and wherein thefirst power monitoring signal includes a measurement at the first time;receiving information about a second network event, wherein the secondnetwork event corresponds to the first device transmitting data at asecond time; obtaining a second power monitoring signal, wherein thesecond power monitoring signal corresponds to a measurement anelectrical property of the power line, and wherein the second powermonitoring signal includes a measurement at the second time; training apower model using the first power monitoring signal and the second powermonitoring signal, wherein the power model is configured to identify thefirst device or a state change of the first device using a powermonitoring signal.

17. The one or more non-transitory computer-readable media of clause 16,wherein the power monitoring signal indicates a current or voltage ofthe power line.

18. The one or more non-transitory computer-readable media of clause 16,wherein the power model comprises a transition model, a device model, ora wattage model.

19. The one or more non-transitory computer-readable media of clause 16,wherein the first network event comprises a broadcast network packet.

20. The one or more non-transitory computer-readable media of clause 16,comprising transmitting the power model to a power monitor in abuilding.

The techniques described above allow for the creation of power modelsfor devices where it may otherwise be difficult to obtain sufficienttraining data to train a power model. For devices with few or withoutany mechanical components (e.g., televisions and computers), there maynot be a lot of variability in the power signatures of the devices. Toobtain an example power signature for such devices, one could manuallychange the state of the device and save the power monitoring signal in awindow around the manual state change, but this process does not scalefor obtaining a large amount of training data or obtaining data for alarge number of devices. By applying the techniques described herein,training data for devices can be obtained through network monitoring.Because this process may not require action by a person, it may thusscale to obtain a large amount of training data and/or training data fora large number of devices. By obtaining training data using networkmonitoring, power models may be created more quickly (since the trainingdata may be obtained more quickly) and the power models may be moreaccurate (since more training data may be available).

Implementation

FIG. 12 illustrates components of some implementations of a computingdevice 1200 that may be used for any of a power monitor or a server thatoperates in conjunction with a power monitor. In FIG. 12 the componentsare shown as being on a single computing device, but the components maybe distributed among multiple computing devices, such as among any ofthe devices mentioned above or among several server computing devices.

Computing device 1200 may include any components typical of a computingdevice, such as one or more processors 1211, volatile or nonvolatilememory 1210, and one or more network interfaces 1212 for connecting tocomputer networks. Computing device 1200 may also include any input andoutput components, such as displays, keyboards, and touch screens.Computing device 1200 may also include a variety of components ormodules providing specific functionality, and these components ormodules may be implemented in software, hardware, or a combinationthereof. Below, several examples of components are described for oneexample implementation, and other implementations may include additionalcomponents or exclude some of the components described below.

Computing device 1200 may include a power event processing component1220 that may be used to process power monitoring signals and determineinformation about devices from the power monitoring signals, such asidentifying devices and device state changes. Computing device 1200 mayinclude a network event processing component 1221 that may be used toprocess data from a computer network and determine information aboutdevices from the network data, such as identifying devices and devicestate changes. Computing device 1200 may include a device identificationcomponent that may be used to identify information about devices (suchas a type of device or make of the device) by using information obtainedfrom power monitoring and/or network monitoring. Computing device 1200may include a device state change component that may be used to identifystate changes of device by using information obtained from powermonitoring and/or network monitoring. Computing device 1200 may have adevice update component 1224 that may be used to update a list ofdevices after devices have been identified or state changes of deviceshave been identified.

Computing device 1200 may include or have access to various data stores,such as data stores 1230, 1231, and 1232. Data stores may use any knownstorage technology such as files or relational or non-relationaldatabases. For example, computing device 1200 may have a power modelsdata store 1230 to store power models or information about power models.Computing device 1200 may have a network models data store 1231 to storenetwork models or information about network models. Computing device1200 may have a device information data store 1232 that may be used tostore information about devices, such as device lists for one or morebuildings.

While only a few embodiments of the present invention have been shownand described, it will be obvious to those skilled in the art that manychanges and modifications may be made thereunto without departing fromthe spirit and scope of the present disclosure as described in thefollowing claims. All patent applications and patents, both foreign anddomestic, and all other publications referenced herein are incorporatedherein in their entireties to the full extent permitted by law.

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software, program codes,and/or instructions on a processor. The processor may be part of aserver, cloud server, client, network infrastructure, mobile computingplatform, stationary computing platform, or other computing platform. Aprocessor may be any kind of computational or processing device capableof executing program instructions, codes, binary instructions and thelike. The processor may be or include a signal processor, digitalprocessor, embedded processor, microprocessor or any variant such as aco-processor (math co-processor, graphic co-processor, communicationco-processor and the like) and the like that may directly or indirectlyfacilitate execution of program code or program instructions storedthereon. In addition, the processor may enable execution of multipleprograms, threads, and codes. The threads may be executed simultaneouslyto enhance the performance of the processor and to facilitatesimultaneous operations of the application. By way of implementation,methods, program codes, program instructions and the like describedherein may be implemented in one or more thread. The thread may spawnother threads that may have assigned priorities associated with them;the processor may execute these threads based on priority or any otherorder based on instructions provided in the program code. The processormay include memory that stores methods, codes, instructions and programsas described herein and elsewhere. The processor may access a storagemedium through an interface that may store methods, codes, andinstructions as described herein and elsewhere. The storage mediumassociated with the processor for storing methods, programs, codes,program instructions or other type of instructions capable of beingexecuted by the computing or processing device may include but may notbe limited to one or more of a CD-ROM, DVD, memory, hard disk, flashdrive, RAM, ROM, cache and the like.

A processor may include one or more cores that may enhance speed andperformance of a multiprocessor. In embodiments, the process may be adual core processor, quad core processors, other chip-levelmultiprocessor and the like that combine two or more independent cores(called a die).

The methods and systems described herein may be deployed in part or inwhole through a machine that executes computer software on a server,cloud server, client, firewall, gateway, hub, router, or other suchcomputer and/or networking hardware. The software program may beassociated with a server that may include a file server, print server,domain server, internet server, intranet server and other variants suchas secondary server, host server, distributed server and the like. Theserver may include one or more of memories, processors, computerreadable media, storage media, ports (physical and virtual),communication devices, and interfaces capable of accessing otherservers, clients, machines, and devices through a wired or a wirelessmedium, and the like. The methods, programs or codes as described hereinand elsewhere may be executed by the server. In addition, other devicesrequired for execution of methods as described in this application maybe considered as a part of the infrastructure associated with theserver.

The server may provide an interface to other devices including, withoutlimitation, clients, other servers, printers, database servers, printservers, file servers, communication servers, distributed servers andthe like. Additionally, this coupling and/or connection may facilitateremote execution of program across the network. The networking of someor all of these devices may facilitate parallel processing of a programor method at one or more location without deviating from the scope ofthe disclosure. In addition, any of the devices attached to the serverthrough an interface may include at least one storage medium capable ofstoring methods, programs, code and/or instructions. A centralrepository may provide program instructions to be executed on differentdevices. In this implementation, the remote repository may act as astorage medium for program code, instructions, and programs.

The software program may be associated with a client that may include afile client, print client, domain client, internet client, intranetclient and other variants such as secondary client, host client,distributed client and the like. The client may include one or more ofmemories, processors, computer readable media, storage media, ports(physical and virtual), communication devices, and interfaces capable ofaccessing other clients, servers, machines, and devices through a wiredor a wireless medium, and the like. The methods, programs or codes asdescribed herein and elsewhere may be executed by the client. Inaddition, other devices required for execution of methods as describedin this application may be considered as a part of the infrastructureassociated with the client.

The client may provide an interface to other devices including, withoutlimitation, servers, other clients, printers, database servers, printservers, file servers, communication servers, distributed servers andthe like. Additionally, this coupling and/or connection may facilitateremote execution of program across the network. The networking of someor all of these devices may facilitate parallel processing of a programor method at one or more location without deviating from the scope ofthe disclosure. In addition, any of the devices attached to the clientthrough an interface may include at least one storage medium capable ofstoring methods, programs, applications, code and/or instructions. Acentral repository may provide program instructions to be executed ondifferent devices. In this implementation, the remote repository may actas a storage medium for program code, instructions, and programs.

The methods and systems described herein may be deployed in part or inwhole through network infrastructures. The network infrastructure mayinclude elements such as computing devices, servers, routers, hubs,firewalls, clients, personal computers, communication devices, routingdevices and other active and passive devices, modules and/or componentsas known in the art. The computing and/or non-computing device(s)associated with the network infrastructure may include, apart from othercomponents, a storage medium such as flash memory, buffer, stack, RAM,ROM and the like. The processes, methods, program codes, instructionsdescribed herein and elsewhere may be executed by one or more of thenetwork infrastructural elements.

The methods, program codes, and instructions described herein andelsewhere may be implemented on a cellular network having multiplecells. The cellular network may either be frequency division multipleaccess (FDMA) network or code division multiple access (CDMA) network.The cellular network may include mobile devices, cell sites, basestations, repeaters, antennas, towers, and the like. The cell networkmay be a GSM, GPRS, 3G, EVDO, mesh, or other networks types.

The methods, programs codes, and instructions described herein andelsewhere may be implemented on or through mobile devices. The mobiledevices may include navigation devices, cell phones, mobile phones,mobile personal digital assistants, laptops, palmtops, netbooks, pagers,electronic books readers, music players and the like. These devices mayinclude, apart from other components, a storage medium such as a flashmemory, buffer, RAM, ROM and one or more computing devices. Thecomputing devices associated with mobile devices may be enabled toexecute program codes, methods, and instructions stored thereon.Alternatively, the mobile devices may be configured to executeinstructions in collaboration with other devices. The mobile devices maycommunicate with base stations interfaced with servers and configured toexecute program codes. The mobile devices may communicate on a peer topeer network, mesh network, or other communications network. The programcode may be stored on the storage medium associated with the server andexecuted by a computing device embedded within the server. The basestation may include a computing device and a storage medium. The storagedevice may store program codes and instructions executed by thecomputing devices associated with the base station.

The computer software, program codes, and/or instructions may be storedand/or accessed on machine readable media that may include: computercomponents, devices, and recording media that retain digital data usedfor computing for some interval of time; semiconductor storage known asrandom access memory (RAM); mass storage typically for more permanentstorage, such as optical discs, forms of magnetic storage like harddisks, tapes, drums, cards and other types; processor registers, cachememory, volatile memory, non-volatile memory; optical storage such asCD, DVD; removable media such as flash memory (e.g. USB sticks or keys),floppy disks, magnetic tape, paper tape, punch cards, standalone RAMdisks, Zip drives, removable mass storage, off-line, and the like; othercomputer memory such as dynamic memory, static memory, read/writestorage, mutable storage, read only, random access, sequential access,location addressable, file addressable, content addressable, networkattached storage, storage area network, bar codes, magnetic ink, and thelike.

The methods and systems described herein may transform physical and/oror intangible items from one state to another. The methods and systemsdescribed herein may also transform data representing physical and/orintangible items from one state to another, such as from usage data to anormalized usage dataset.

The elements described and depicted herein, including in flow charts andblock diagrams throughout the figures, imply logical boundaries betweenthe elements. However, according to software or hardware engineeringpractices, the depicted elements and the functions thereof may beimplemented on machines through computer executable media having aprocessor capable of executing program instructions stored thereon as amonolithic software structure, as standalone software modules, or asmodules that employ external routines, code, services, and so forth, orany combination of these, and all such implementations may be within thescope of the present disclosure. Examples of such machines may include,but may not be limited to, personal digital assistants, laptops,personal computers, mobile phones, other handheld computing devices,medical equipment, wired or wireless communication devices, transducers,chips, calculators, satellites, tablet PCs, electronic books, gadgets,electronic devices, devices having artificial intelligence, computingdevices, networking equipment, servers, routers and the like.Furthermore, the elements depicted in the flow chart and block diagramsor any other logical component may be implemented on a machine capableof executing program instructions. Thus, while the foregoing drawingsand descriptions set forth functional aspects of the disclosed systems,no particular arrangement of software for implementing these functionalaspects should be inferred from these descriptions unless explicitlystated or otherwise clear from the context. Similarly, it will beappreciated that the various steps identified and described above may bevaried, and that the order of steps may be adapted to particularapplications of the techniques disclosed herein. All such variations andmodifications are intended to fall within the scope of this disclosure.As such, the depiction and/or description of an order for various stepsshould not be understood to require a particular order of execution forthose steps, unless required by a particular application, or explicitlystated or otherwise clear from the context.

The methods and/or processes described above, and steps thereof, may berealized in hardware, software or any combination of hardware andsoftware suitable for a particular application. The hardware may includea general purpose computer and/or dedicated computing device or specificcomputing device or particular aspect or component of a specificcomputing device. The processes may be realized in one or moremicroprocessors, microcontrollers, embedded microcontrollers,programmable digital signal processors or other programmable device,along with internal and/or external memory. The processes may also, orinstead, be embodied in an application specific integrated circuit, aprogrammable gate array, programmable array logic, or any other deviceor combination of devices that may be configured to process electronicsignals. It will further be appreciated that one or more of theprocesses may be realized as a computer executable code capable of beingexecuted on a machine readable medium.

The computer executable code may be created using a structuredprogramming language such as C, an object oriented programming languagesuch as C++, or any other high-level or low-level programming language(including assembly languages, hardware description languages, anddatabase programming languages and technologies) that may be stored,compiled or interpreted to run on one of the above devices, as well asheterogeneous combinations of processors, processor architectures, orcombinations of different hardware and software, or any other machinecapable of executing program instructions.

Thus, in one aspect, each method described above and combinationsthereof may be embodied in computer executable code that, when executingon one or more computing devices, performs the steps thereof. In anotheraspect, the methods may be embodied in systems that perform the stepsthereof, and may be distributed across devices in a number of ways, orall of the functionality may be integrated into a dedicated, standalonedevice or other hardware. In another aspect, the means for performingthe steps associated with the processes described above may include anyof the hardware and/or software described above. All such permutationsand combinations are intended to fall within the scope of the presentdisclosure.

All documents referenced herein are hereby incorporated by reference.

What is claimed is:
 1. A system for training a power model foridentifying devices or device state changes, the system comprising: atleast one computer comprising at least one processor and at least onememory, the at least one computer configured to: receive informationabout a first network event, wherein the first network event correspondsto a first device in a first building transmitting data at a first time;determine that the first device changed state using the informationabout the first network event; obtain a first power monitoring signal,wherein the first power monitoring signal corresponds to a measurementof an electrical property of a power line in the first building, andwherein the first power monitoring signal includes a measurement at thefirst time; receive information about a second network event, whereinthe second network event corresponds to a second device in a secondbuilding transmitting data at a second time; determine that the seconddevice changed state using the information about the second networkevent; obtain a second power monitoring signal, wherein the second powermonitoring signal corresponds to a measurement of an electrical propertyof a power line in the second building, and wherein the second powermonitoring signal includes a measurement at the second time; train apower model using the first power monitoring signal and the second powermonitoring signal, wherein the power model is configured to identify adevice or a state change of a device using a power monitoring signal;and transmit the power model to a power monitor in a third building. 2.The system of claim 1, wherein the first device and the second deviceare the same type of device, have the same manufacturer, or have thesame version.
 3. The system of claim 1, wherein the at least onecomputer comprises a first power monitor in the first building, a secondpower monitor in the second building, and a server computer.
 4. Thesystem of claim 1, wherein the at least one computer is configured to:obtain a third power monitoring signal, wherein the third powermonitoring signal corresponds to a measurement of an electrical propertyof a power line in the third building; and process the third powermonitoring signal with the power model to determine that a third devicechanged state.
 5. The system of claim 1, wherein the at least onecomputer is configured to: transmit a request for information to thesecond device; and wherein the information about the second networkevent is received in response to the request for information.
 6. Thesystem of claim 1, wherein the at least one computer is configured to:receive information about a plurality of network events, wherein eachnetwork event corresponds to the first device transmitting data; anddetermine that the first device changed state using the informationabout the plurality of network events.
 7. The system of claim 1, whereinthe at least one computer is configured to determine that the firstdevice changed state by (1) processing the information about the firstnetwork event with a plurality of network models, and (2) selecting ahighest scoring network model.
 8. A method for training a power modelfor identifying devices or device state changes, the method comprising:receiving information about a first network event, wherein the firstnetwork event corresponds to a first device transmitting data at a firsttime; obtaining a first power monitoring signal, wherein the first powermonitoring signal corresponds to a measurement of an electrical propertyof a power line, and wherein the first power monitoring signal includesa measurement at the first time; receiving information about a secondnetwork event, wherein the second network event corresponds to the firstdevice transmitting data at a second time; obtaining a second powermonitoring signal, wherein the second power monitoring signalcorresponds to a measurement of an electrical property of the powerline, and wherein the second power monitoring signal includes ameasurement at the second time; and training a power model using thefirst power monitoring signal and the second power monitoring signal,wherein the power model is configured to identify the first device or astate change of the first device using a power monitoring signal.
 9. Themethod of claim 8, comprising: determining that the first device changedstate using the information about the first network event; anddetermining that the first device changed state using the informationabout the second network event.
 10. The method of claim 8, comprisingtransmitting the power model to a power monitor in a building.
 11. Themethod of claim 8, wherein the first network event comprises a broadcastnetwork packet.
 12. The method of claim 8, wherein the information aboutthe first network event comprises a time of the first network event. 13.The method of claim 8, comprising: determining that the first powermonitoring signal comprises a first power event and a second powerevent; determining that the first power event corresponds to the firstdevice changing state; and training the power model using the firstpower event.
 14. The method of claim 13, wherein determining that thefirst power event corresponds to the first device comprises: computingfirst features for the first power event and second features for thesecond power event; and processing the first features and the secondfeatures with a mathematical model or clustering the first features andsecond features.
 15. The method of claim 8, wherein the first device isin a first building and the method comprising: receiving informationabout a third network event, wherein the third network event correspondsto a second device in a second building transmitting data at a thirdtime; obtaining a third power monitoring signal, wherein the third powermonitoring signal corresponds to a measurement of an electrical propertyof a power line in the second building, and wherein the third powermonitoring signal includes a measurement at the third time; and trainingthe power model using the third power monitoring signal.
 16. One or morenon-transitory computer-readable media comprising computer executableinstructions that, when executed, cause at least one processor toperform actions comprising: receiving information about a first networkevent, wherein the first network event corresponds to a first devicetransmitting data at a first time; obtaining a first power monitoringsignal, wherein the first power monitoring signal corresponds to ameasurement of an electrical property of a power line, and wherein thefirst power monitoring signal includes a measurement at the first time;receiving information about a second network event, wherein the secondnetwork event corresponds to the first device transmitting data at asecond time; obtaining a second power monitoring signal, wherein thesecond power monitoring signal corresponds to a measurement of anelectrical property of the power line, and wherein the second powermonitoring signal includes a measurement at the second time; andtraining a power model using the first power monitoring signal and thesecond power monitoring signal, wherein the power model is configured toidentify the first device or a state change of the first device using apower monitoring signal.
 17. The one or more non-transitorycomputer-readable media of claim 16, wherein the power monitoring signalindicates a current or voltage of the power line.
 18. The one or morenon-transitory computer-readable media of claim 16, wherein the powermodel comprises a transition model, a device model, or a wattage model.19. The one or more non-transitory computer-readable media of claim 16,wherein the first network event comprises a broadcast network packet.20. The one or more non-transitory computer-readable media of claim 16,comprising transmitting the power model to a power monitor in abuilding.